Last weekend, Y Combinator packed the Chase Center and handed the floor to the people actually building the future of AI.

Over 30,000 founders applied, from 120+ countries. Acceptance rate: under 1%. And the ones who got in? Jensen Huang told them flat out: “If you’re here, you’re gonna make it.”

Two days. Ten stages. Jensen Huang, Sam Altman, Boris Cherny, Jeff Dean, Waymo’s Dmitri Dolgov, and more. each one dropping the kind of insight most people pay years of tuition (or failed startups) to learn.

I sat through all of it, read the notes, the transcripts, and every founder’s live thread, so you don’t have to. Inside you’ll find the key takeaways from these speakers:

• Garry Tan (President, YC)

• Jensen Huang (Founder and CEO, NVIDIA)

• Sam Altman (Co-founder and CEO, OpenAI)

• Boris Cherny (Head of Claude Code, Anthropic)

• Jeff Dean (Chief Scientist, Google DeepMind)

• Dmitri Dolgov (Co-founder and CEO, Waymo)

• Alexandr Wang (Chief AI Officer at Meta)

• Patrick Collison (Co-founder and CEO, Stripe)

• Chelsea Finn (Co-founder, Physical Intelligence)

• Peter Steipete (OpenClaw)

Let’s get into it!

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📈 Startup Playbooks
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🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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The strange part is that CEO Amjad Masad does not treat that number as a goal at all.

He warns that most AI companies posting growth like this are quietly dying underneath it, with churn approaching 100%, and that a headline like his own can hide a business that is falling apart.

So we went through hours of Masad’s interviews to find out what actually drove the run.

What follows is the sequence of moves behind the number: the layoff that turned into an all-in bet, the customer nobody else was chasing, the boring infrastructure that became the real moat and the honest way to read AI growth, including your own.

Inside you will find:

1. The Layoff That Became an All-In Bet on Agent

2. Build the Product That Gets Better When You Swap the Model

3. Chase the Billion Non-Engineers, Not the Developers

4. The Real Moat Is Two Years of Boring Infrastructure

5. Story Is a Growth Channel, Not a PR Function

6. How to Read AI Growth Honestly

7. What to Steal: The 6-Move Replit Playbook

This issue is available exclusively to paid subscribers!

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Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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Instead of watching 2 hours of Netflix tonight, study this 40-minute masterclass from the founder of a $20B China AI company.

It's the clearest explanation I've seen of how Agent Swarms and AI systems actually work at scale.

I broke it down into the most actionable insights so you can apply them directly.

Here’s what you can learn today:

1. Why Kimi scales three dimensions at once instead of just adding tokens

2. Why token efficiency raises the ceiling on intelligence, not just the cost

3. Why long context is the capability that makes agents runnable for weeks

4. The 3 reward functions that stop agent swarms from collapsing or cheating

5. How Kimi fused all three dimensions into K2.5 (and why vision made text smarter)

6. The 24% token-efficiency jump hiding in Kimi’s next architecture

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates

↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks

↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library

↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools

↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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The company reports going from $0 to over $100M in annualized revenue in roughly 9 months while selling an integrated RL post-training stack. They then raised a $130M Series A led by Radical Ventures with NVIDIA, Intel Capital, and Dell Capital.

We broke down the exact wedge, packaging, and customer-proof sequence behind that run so you can steal the playbook, not just admire the number.

In this guide you’ll find:

1. What Prime Intellect actually sells: the Open Superintelligence Stack, layer by layer

2. The open-source wedge: how the Environments Hub reached 1,000+ environments before Lab launched

3. The positioning bet that unlocked demand: how ‘RL breaks open the frontier’ won teams away from closed-lab APIs

4. The 4 growth levers that drove 6,000+ customers and $100M ARR in under a year

5. The named-customer proof machine (Ramp, Arcee, Zapier) and how it replaced a sales team

6. The $130M Series A: who backed it, at what traction, and the angel list

7. 5 lessons to steal from Prime Intellect’s 9-month run

👋 Just a quick note before you continue!

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

Annual paid subscribers now unlock exclusive deals on the AI tools founders actually use every day.

Here’s what’s live on the perks page right now:

• Framer: 1 year free

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Elon Musk does not outperform entire industries because he works longer hours, hires more people or has access to better technology.

He operates his companies using a distinct system for questioning assumptions, removing complexity, accelerating learning, identifying exceptional talent and concentrating resources on the biggest constraint.

To understand how that system actually works, I studied three of the clearest breakdowns of Musk’s operating methods:

David Senra’s 110-minute How Elon Thinks conversation with Eric Jorgenson, who spent five years and thousands of hours studying Musk to write The Book of Elon.

Relentless’s 102-minute conversation with Sequoia partner Shaun Maguire, Why Elon Outcompetes Everyone, which explores Musk’s talent selection, capital allocation, risk tolerance and ability to compound knowledge faster than his competitors.

And Andrej Karpathy’s talk at Sequoia AI Ascent, where the former Tesla AI leader explained what it was actually like to operate inside one of Musk’s companies—and how small, highly technical teams, extreme ownership and direct access to the underlying work shaped Tesla’s execution.

Together, they reveal something more useful than another collection of Elon stories.

They reveal the Elon Operating System: the repeatable principles Musk uses to build companies that move faster, learn faster and achieve outcomes that initially appear physically or economically impossible.

In this guide, you’ll learn:

1. The five-step build algorithm, in the exact order Musk runs it

2. How Musk engineers his companies to fail on purpose

3. How Musk identifies talent and creates extreme accountability

4. Why Musk keeps teams small, technical and close to the work

5. The mission-and-pain layer beneath the operating system

6. How Musk allocates capital and attacks constraints

7. The portable Elon OS checklist

👋 Just a quick note before you continue!

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

Annual paid subscribers now unlock exclusive deals on the AI tools founders actually use every day.

Here’s what’s live on the perks page right now:

• Framer: 1 year free

• MITO: 60% off for 6 months

• Gojiberry: 50% off for 6 months

• Cubic: 50% off your first month

• Omnia: 20% off

• Granola: 1 month free

• Slashy: 1 month free

• QuiverAI: 1 month free

• Throxy: 50% off for 3 months

These deals are worth more than $3,000.

Get 30% off forever

Here’s a good place to start:

🤖 AI Agent Templates

↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks

↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library

↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools

↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

The rest of the article is only available to premium subscribers.

1. The 5-step build algorithm, in the exact order Musk runs it (and why running it backwards nearly killed Tesla and Starlink)

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This morning Sifted reported that Lovable is in talks to raise $300 million at a $13.2 billion post-money valuation, with Menlo Ventures set to lead the round.

If it closes at those terms, the company will have doubled its price tag in roughly six months!

Sit with the timeline for a second, because the pace is the whole story:

• Oct 2024 → raises $7.5M (Hummingbird Ventures, byFounders)

• Feb 2025 → raises $15M (Creandum, Visionaries Club)

• Jul 2025 → becomes a unicorn, $200M Series A at $1.8B (Accel, 20VC, Creandum, Hummingbird, byFounders, Visionaries Club, Evantic)

• Dec 2025 → raises $330M at $6.6B (Google, Menlo Ventures, NVIDIA, Salesforce Ventures, Databricks Ventures, Atlassian Ventures, HubSpot Ventures, T.Capital, Khosla Ventures, DST Global, EQT Growth, Kinship Ventures, Accel, Creandum, Evantic)

• Jul 2026 → reported talks at $13.2B

That is five financings in about twenty months, each at a higher multiple than the last, with a founder who at one point simply stopped answering the term sheets landing in his inbox at a $4 billion valuation because he didn’t feel like raising yet.

Most founders experience fundraising as a thing that happens to them. Lovable built a machine that made investors show up before it asked, compete once they were there and accept terms that got worse for them with every passing quarter.

Inside you will find:

🟧 The demand machine that took Lovable from a $7.5M pre-seed to a reported $13.2B in twenty months

🟧 The full details of all five rounds and why each fund and angel was chosen

🟧 The angel-first move that buys competence and distribution, not just a check

🟧 The public ARR cadence that made investors chase before Lovable ever asked

🟧 What Osika did when unsolicited $4 billion offers hit his inbox

🟧 How the product closed a $200M round before the pitch meeting even started

🟧 The investor-sequencing map for who to raise from at each stage

🟧 The six channels that put your growth in front of the people who write the checks

The next era of GTM runs on Attio.

It meets you where you work, compounds every customer signal into context, then acts on it so you can move fast, stay sharp, and scale without breaking. With Attio’s new workflows, run revenue agents across every account, so you can:

• Score every lead for fit and priority

• Catch renewals before they slip

• Get answers about your business in seconds

Loved by high-growth startups like Granola, Modal, and Railway, Attio is the agentic CRM for winning teams.

Try Now (For Free)

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Here’s a good place to start for fundraising:

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors
↳ How ElevenLabs Grew From $0 to $200M ARR in 2 Years + Their Pre-Seed Deck
↳ 70 Pitch Decks That Raised Over $1 Billion in 2024
↳ Anthropic Pitch Deck: This 10 Slides Predicted a $350,000,000,000 Company

💰 Investor Database & Tools
↳ The Family Office List
↳ How to Get Into YC: The Full F25 Application Pack
↳ The 10 Excel Templates Every SaaS & AI Founder Needs to Build, Survive, and Scale
↳ Creandum fundraising Toolbox, from Seed to Series A

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Here is what they say works:

• in-house creative, meaning video and editorial made by people who did this for a living

• owned channels, meaning an X account, a newsletter and a podcast

• A full-service team that runs launches end to end

The message to a founder is not “look what a16z offers” but rather “this is where you should be insisting too”.

The obvious objection is that you cannot borrow the team. No video crew, no editorial desk, no launch unit, no million-follower account. So it is easy to file New Media under “works if you already have a billion-dollar fund” and move on. That is the mistake.

The same motions are now things a two-person company can run on a normal week, at a smaller scale, if you know what to build and in what order. This guide is that order: what a16z is telling you works, why it works and the practical version of each motion you can actually run, with the tools that make it possible.

Inside you will find:

1. What a16z Means by New Media and the Channels They Bet On

2. How to Run an In-House Video Team of One

3. How to Write the Essays That Earn You Signal

4. How to Build Owned Channels That Guarantee You Distribution

5. How to Run a Launch That Drives Pipeline

6. How to Turn Your Network Into a Hiring and Signal Machine

7. How to Run the Whole Engine on a Founder’s Schedule

👋 Just a quick note before you continue!

Building great AI systems and agents is quickly becoming one of the most important advantages a startup can have. So we’ve been building non-stop and this will become a much bigger part of PMF going forward.

From now on, as a premium subscriber, you’ll get access not just to the best resources on fundraising and growth (160+ Playbooks, 65+ Success Stories, 30+ Pitch Deck Collections, 25+ Investor Resources), but also:

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The rest of the article is only available to premium subscribers.

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Lovable is not growing because it found one clever channel.

It is growing because it built a system where:

• the product creates delight

• delight creates sharing

• sharing creates trust

• trust creates growth

In Elena Verna’s framing, growth is a trust problem now.

When software becomes easier to build, functionality stops being enough. People can copy features. They can build alternatives. What they cannot copy as easily is:

• trust

• brand

• speed

• relevance

• emotion

• community energy

• product-led word of mouth

That is the real growth engine.

We broke down Lovable’s growth into a system that can be understood and, in parts, applied whether you’re early or already scaling.

1. Why growth is becoming a trust problem (not a channel problem)

2. How to use your product as the main growth channel

3. Why you need a “minimum lovable product,” not just a functional one

4. How to use founder-led social to drive early traction

5. How to turn employees into a distribution engine

6. Why AI-native companies blur roles (and why it matters)

7. Why avoiding the biggest mistake in early-stage growth (paid too early)

8. How to sequence organic and paid growth the right way

9. Why most communities fail (and how to build one that works)

10. How to turn users into your most effective growth channel (UGC)

11. How to define activation around real value, not vanity metrics

12. How to use continuous launches to drive retention and relevance

13. How to stay top-of-mind in fast-moving markets

14. How to design monetization for bursty AI usage

15. Why brand becomes critical as products commoditize

16. How to use brand and offline campaigns effectively (and when)

17. Why leveraging creators as a growth channel

18. How to turn free product moments into growth campaigns

19. Why speed acts as a trust signal

20. How to compete with incumbents using speed, culture, and distribution

Why it’s valuable

This guide connects a lot of scattered ideas into a more coherent model.

You can use this to:

• think about product as distribution, not just utility

• treat free usage as awareness, not just lost revenues

• prioritize organic pull before scaling paid

• design for sharing and visibility, not just usage

• avoid scaling a system that hasn’t earned trust yet

The full breakdown is available for paid subscribers. If you’re not one yet, you can join here:

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How is it even remotely normal that a 19-year-old scaled an app to ~$50M ARR in 18 months…

…then sold 100% of it to the category leader…

…with zero VC funding???

No seed. No Series A. All bootstrapped.

Just raw distribution and the most ruthless execution I’ve ever seen from any founder his age.

And now he just dropped an interview where he lays out exactly how they did it.

The actual mechanics: Attribution hacks, creative frameworks, campaign structures, UGC systems…

This is not an “AI startup” story.

This is a masterclass in modern consumer growth 🔥

Cal AI is a consumer app that lets you take a photo of your food and instantly get calories and macros.

Just:

📸 Snap → 📊 Calories + macros → Done.

That’s it.

In one of the most competitive consumer categories on earth (calorie tracking) this 19-year-old founder built this to:

• $30M revenue in 2025

• $5.7M revenue in January alone

• ~$50M ARR / run-rate

• Zero funding

• Then sold 100% of it to MyFitnessPal

Eighteen months. Here’s how:

What We’ll Break Down

1. Start With a Product That Demonstrates Itself in 2 Seconds

Why Cal AI built a product that demonstrates itself instantly on video.

2. Distribution Before Product

How they validated a content ecosystem before writing a single line of code.

3. The Brutal Early Days: 500 DMs → 2 Creators

How manual influencer outreach became their first growth engine.

4. The Economics That Made Influencer Marketing Profitable

The RPM vs CPM framework that made creator marketing profitable.

5. The Negotiation Tactics To Lower Creator Costs

How bundling, view guarantees, and DMs cut influencer costs dramatically.

6. The UGC Creative Strategy & How to Copy Them (INSANE🔥)

Why native content beats ads — and how Cal AI engineered viral creator videos.

7. Turning the Comment Section Into a Funnel

How pinned comments and fast replies turned curiosity into installs.

8. Building a Creator Discovery Machine

How they trained TikTok’s algorithm to constantly surface new influencers.

9. Scaling to 150 Creators

Why retainers created predictable distribution and lower acquisition costs.

10. The Paid Ads Multiplier: $2M/year to $50M/year

How influencer videos became the creative engine for profitable Meta and TikTok ads.

11. Using Apple Search Ads to Attack Competitors

Using Apple Search Ads to intercept competitor demand.

12. Understand & Optimize Conversion Engineering

How onboarding psychology and trial design increased subscription conversion.

Apply to The Pitch by Deel now

A teenager built a consumer subscription app to ~$50M run-rate in a year and a half, bootstrapped, in one of the most competitive categories on earth.

And then sold it to his biggest competitor. explain here what it is

Let’s break down exactly what he revealed, and why this might be one of the most instructive consumer growth case studies of the last few years 🔥

How Cal AI Went From a High School Project to ~$50M ARR 🔥

The Exact Growth Systems They Used (In Order)

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Everyone is arguing about how powerful AI is getting. Wrong conversation!

What matters now is where leverage survives once intelligence is cheap, and where it doesn’t.

This week, in OpenAI’s Town Hall, Sam Altman wasn’t making announcements, but he was outlining constraints. The kind that quietly determine which startups work and which ones never compound.

Below are 12 moments from that conversation that actually matter if you’re building: reordered, compressed, and interpreted for people who care about product, distribution, and durability.

First impressions matter.

With Framer, early-stage founders can launch a beautiful, production-ready site in hours. No dev team, no hassle.

Join hundreds of YC-backed startups who launched here and never looked back.

Pre-seed and seed-stage startups new to Framer can enjoy:

• One year free: Save $360 with a full year of Framer Pro, free for early-stage startups.

• No code, no delays: Launch a polished site in hours, not weeks, without hiring developers.

• Built to grow: Scale your site from MVP to full product with CMS, analytics, and AI localization.

• Join YC-backed founders: Hundreds of top startups are already building on Framer.

Apply to claim your free year →

What We’ll Break Down 🔥

1. Jevons Paradox for AI: Cheaper Intelligence = More Software

2. WhyGTM Is Still the Bottleneck

3. When the Platform Doesn’t Know the Interface
Why OpenAI’s uncertainty signals category creation, not stability.

4. The 100× Cost Curve Is the Real Disruption
How infrastructure deflation unlocks entire categories before features do.

5. From Tools to Solved Problems
Why continuously generated software changes the unit of value.

6. The Founder Trap: Betting on Future Model Upgrades
Why relying on model progress is not a moat.

7. The Agent Trust Layer: Why Verification > Autonomy

8. Integrations Are Not Defensibility
As models learn tools instantly, advantage shifts to workflows and proprietary data.

9. The Hidden Risk Curve of Agents
Permission creep, rare failures, and the rise of monitoring infrastructure.

10. Memory as the New Switching Cost
Why persistent context, not raw intelligence, compounds defensibility.

11. Org Design in an Abundance Era
Leverage per employee becomes the only metric that matters.

12. Assume 100× Everything
How to think like a builder in a world where intelligence is no longer scarce.

Let’s get into this 🔥

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Most founders don’t fail because the product sucks.

They fail because they keep acting like the best employee when the company needs a CEO.

At scale, “being productive” stops meaning what you can do today. It means what the company can do without you. If you don’t make that switch, you become the bottleneck. hen the board, the market, or burnout makes the decision for you.

This isn’t motivational. It’s statistical. In a study of 1,156 VC-backed U.S. IPOs, 40.8% changed CEOs between the first VC round and the IPO. And HBR notes founder-CEO transitions are 2–3x more likely to fail or cause a performance drop than transitions between nonfounder CEOs.

So this guide is about one thing: killing the “founder mode” habits that stall growth, and replacing them with CEO systems.

It includes:

1. The 4 CEO fundamentals founders learn too late

2. The step-by-step process to remove yourself as the bottleneck

PMF is read by more than +1000 different VC firms & tens of thousands of the fastest growing startup founders including multiple YC founders.

Want to put your company in front of them?

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1. The 4 CEO fundamentals founders learn too late

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Naval Ravikant predicted a future where small, specialized startups dominate niche problems.

We’re now seeing that vision come to life with AI Solopreneurs: professionals who use their expertise in tandem with AI to produce massive results: all under a single-person operation.

With Framer, early-stage founders can launch a beautiful, production-ready site in hours. No dev team, no hassle.

Join hundreds of YC-backed startups who launched here and never looked back.

Pre-seed and seed-stage startups new to Framer can enjoy one year free: Save $360 with a full year of Framer Pro, free for early-stage startups.

Apply to claim your free year →

Subscribe now

What’s an AI Solopreneur?

It’s pretty simple: imagine a consultant or freelancer who combines human expertise with AI tools—enabling them to handle the work of an entire team without building a massive organization.

They enjoy:

• Top-tier results for clients at competitive rates

• Manage multiple projects without burnout

• Easier scaling—AI handles tedious tasks so you can focus on what really matters

To productize yourself is to turn your skills, experiences, and insights into repeatable, marketable offerings—like coaching programs, digital courses, or done-for-you services.

By combining this approach with AI-driven automations, you can handle more clients, solve bigger problems, and truly work less while delivering great value.

Three Key Pillars: Marketing, Craft & AI

Despite the tech transformation, the fundamentals remain: you must excel at Marketing and at a specific Craft.

1. Marketing

Step 1: Choose Your Tribe (Your Niche)

Pick a hyper-specific niche that resonates with both your skills and passions. Examples:

• “AI-driven sales funnel optimization for B2B SaaS”

• “AI-powered copywriting for health & wellness brands”

• “Fitness coaching for busy professionals”

When you specialize, you stand out, command higher rates, and attract clients who see real value in your expertise.

This is a great example of the latter. Blogging for devs: a course of blogging for developers. Super niche in:
1. The target
2. The skill it teaches

Step 2: Find Where Your Tribe Hangs Out

• Online Communities: LinkedIn groups, Subreddits, Slack channels, Discord servers

• Social Media: X (Twitter), LinkedIn, Instagram, or TikTok—only pick the ones your ideal clients actually use

• Offline Events: Industry expos, local meetups, conferences—yes, old-school networking still works

Step 3: Create (Market)

2. The Craft

The idea is pretty simple:

Choose the skill/craft you’ll be monetizing and practice it as much as possible to become as good as possible.

If you work on it enough you can become the best of the world in less than 5 years.

Now, up to this point you have done the same any small professional would do to get by, but how can you scale this?

3. Leverage AI to Multiply Your Output x50

Imagine having 50 virtual assistants working around the clock. AI tools can help you:

• Learn how to Generate Content at Scale: Use ChatGPT or other large language models to draft blog posts, email campaigns, or social media updates. Then edit, refine, and humanize that content so it remains authentic to you.

  For example: I created a GPT to build Linkedin Viral Infographics like this👇

• Automate Research: Tools like Bing Chat or specialized web-scraping AIs can sift through data or trends in minutes—what would have taken you hours (or days) now takes moments.

• Streamline Communication: Let AI handle meeting summaries, customer service chatbots, or quick email replies—so you’re free to focus on creative or strategic tasks.

• Optimize Workflows: Link AI with no-code platforms (e.g., Zapier, Make) to handle repetitive tasks (scheduling, file organization, lead capturing), reducing human error and saving you massive time.

The result? You can deliver 50x more value—creating proposals, prototypes, and entire marketing campaigns in a fraction of the time.

While AI churns out drafts, data, or routine follow-ups, you refine high-level strategy and maintain the human touch. This synergy between tech and talent is the secret sauce for standing out in a crowded market.

Access Now 200 Ways to Make Money with AI

Check it out with the free trial (no strings attached), or jump straight into premium if you’re ready for the full scoop👇

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(WARNING🚨: This is a brutally direct and practical execution guide)

Most startup advice on X or LinkedIn fails for one simple reason: it’s written to sound smart and get views, not for getting results.

This is different.

This is a step-by-step playbook for going from idea → first revenue in under 21 days, built by compiling what actually worked early for companies like Reddit, Stripe, Buffer, and Superhuman, alongside the early stage advice of Paul Graham.

It’s designed to be executed by one person: no team, engineers nor audience.

Every step is specific backed by what the founders of great companies did.
Every tool is named.
Every decision has a clear “move on” or “stop” signal.

If you execute this properly, one of two things will happen within 21 days:

1. Someone pays you for what you’re building

2. You get hard proof of why they won’t, before wasting months building the wrong thing

Both of these are incredibly valuable if you want to build long-term.

What you’ll actually get from this guide

Most founders duct-tape an MVP, demo it to friends who won’t say no, call it “validation,” and forget about it in under a week.

This is not that. By the end, you will have:

• a clearly defined buyer (real people, real companies)

• a priced offer you’ve said out loud to prospects

• a list of 50–100 potential customers you personally contacted

• transcripts of real conversations with buyers

• at least one explicit yes or no to paying

This guide is for solo founders, first-time builders, and operators validating an idea who are tired of vague “just ship” advice with no instructions.

First impressions matter.

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The 21-Day Breakdown:

Days 0–3: Kill or Commit 🔪

How to FIND and validate the problem, define the buyer, and decide if the idea deserves 21 days of your life. Follow Paul Graham’s core advice.

Days 4–5: Define the Offer & Price It 📦

Turn the idea into something concrete people can say yes or no to. Follow Buffers playbook regarding pricing before launching.

Days 6–13: Build the Smallest Sellable Version 🧱

Create only what’s needed to deliver value, NOTHING more. Learn from Reddit’s early “product faking” strategy.

Days 14–16: Get in Front of Real Buyers 💬

How to find and target specific companies, message potential customers, and start conversations organically. Stripe’s playbook: how they talked to users before thinking about sales.

Days 16–21: CLOSE & Deliver 🤝💰

Close, close, close. Ask for money, onboard personally, and extract the truth from outcomes. Follow Superhuman’s playbook: onboard users personally and how they charged from day one

Lets get to it🔥

Days 0–3: Kill or Commit

Day 0: How to Find a Real Problem

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AI is about to split companies into 2 categories:

1) The ones still paying 2020 prices for 2026 output
2) The ones rewriting their cost structure with AI

Because what used to take a $100,000 budget now costs a few hundred bucks.

Not in theory. In practice:

• Design → from “weeks + agency” to “hours + tools”

• Copy → from “copywriter + revisions” to “drafts in minutes”

• Research → from “analyst time” to “instant synthesis”

• Sales upgrades → from “enablement team” to “always-on coaching + personalization”

• Customer support → from “more headcount” to “resolution automation”

Whole teams are getting compressed into software.

So this isn’t “tech trend” content.

This is your P&L getting rewritten.

And the most dangerous part?

Your competitor isn’t waiting for a perfect strategy deck.
They’re learning this right now, quietly, every day:

• Which workflows to automate

• Which roles to augment

• Which costs to delete

• Which outputs to 10x

In 12 months, a lot of markets will look “the same” from the outside…

…but one company will be running with a cost base that makes everyone else uncompetitive.

Hey everybody, welcome to PMF.

In this newsletter you’ll find the tools and ways some of the smartest founders are using to go create content in multiple formats and distribute it massively at a fraction of the cost of what it used to be.

1. AI Video generation tools

2. How AI Influencers generating millions of views

3. How to distribute your content with UGC (how ElevenLabs is doing it)

   

Subscribe now

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Trending right now: The Data Room Template VCs love, 27 Most Promising AI Startup Pitch Decks Backed by Top Investors in 2025

1) AI Video Generation Tools

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Great founders study problems.

Airbnb didn’t start with “let’s build a marketplace for short-term rentals.”
Stripe didn’t start with “let’s build payments infrastructure.”
OpenAI didn’t start with “let’s ship a chatbot.”

They all started with something much more primitive:

“This is broken. And nobody has fixed it properly.”

In this piece, I’ll do two things:

1. Break down the core problems that inspired some of the biggest tech companies in the world (Airbnb, Stripe, Amazon, OpenAI)

2. Share 15 unsolved problems that I believe can still produce decacorns heading into 2026

If you’re a founder, this is how you should be training your brain.

Join OpenAI for Startups

Sponsor Product Market Fit & get your product in front of thousands of founders worldwide? Reach out to g@guillermoflor.com

Trending right now: The Data Room Template VCs love, 27 Most Promising AI Startup Pitch Decks Backed by Top Investors in 2025

Part I – The Problems Behind Iconic Startups

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The X algorithm is a pipeline. A very literal set of steps:

• pick a bunch of tweets

• throw most of them away

• predict what you’ll do on the rest

• score them

• show you the top few

• learn from what you did

We went through the actual system that powers the For You feed and translated it into normal language.

If your grandma can understand how Netflix recommends shows, she can understand this.

In this newsletter you’ll get the full playbook to go viral on X + 50 tweet templates designed for the actions X rewards

1. How X builds a “taste profile” for every user

2. How X pulls tweets from two different buckets

3. How out-of-network discovery really works

4. Why most tweets never even get scored

5. How X predicts what a user will do when they see a tweet

6. Why replies and reposts matter more than likes

7. How negative signals quietly destroy reach

8. Why posting too much can actually hurt your distribution

9. Why the first 15–30 minutes decide a tweet’s fate

10. How the feedback loop compounds winners

11. A simple founder playbook you can actually follow

12. 50 tweet templates designed for the actions X rewards

Let’s get to it 🔥

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Trending right now: How Base44 was bootstrapped and sold for $80M in 9 months

Get access to this and much more with the PMF subscription

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🖼️ +50 Pitch Decks of World’s Most Sucessful Startups

🖼️ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors in 2025

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Hey everyone 👋

If you’ve been anywhere near tech or marketing over the past few months, you’ve probably heard the term GEO thrown around nonstop.

• “LLM SEO”

• “Get your startup into ChatGPT”

• “Optimize for AI answers”

And now you’ve likely seen Sam Altman’s latest tweet: OpenAI is starting to test ads inside ChatGPT.

At first glance, this feels like just another monetization update. Think again maybe.

This is the moment GEO stops being a niche growth hack and starts becoming a core distribution channel. Real incentives, real budgets, and real winners. Same (or more) than what SEO has been the past 10 years.

Today’s post is not about:

• how to “rank” in ChatGPT,

• or quick tricks to get mentioned once.

Instead, we’re going to cover three things that actually matter now:

1. What GEO is and how it really works under the hood (and why most advice online is wrong)

2. Why ads accelerate GEO instead of killing it

3. What you can do today to win AI-native visibility over the next 12–24 months

If you’re building or marketing a product, this shift matters more than any Google update in the last decade, trust me.

Let’s break it down.

Join OpenAI for Startups

Sponsor Product Market Fit & get your product in front of thousands of founders worldwide? Reach out to g@guillermoflor.com

Trending right now: The Data Room Template VCs love, 27 Most Promising AI Startup Pitch Decks Backed by Top Investors in 2025

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